首页> 外文期刊>Microchemical Journal: Devoted to the Application of Microtechniques in all Branches of Science >Non-destructive screening method for detecting the presence of insects in sorghum grains using near infrared spectroscopy and discriminant analysis
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Non-destructive screening method for detecting the presence of insects in sorghum grains using near infrared spectroscopy and discriminant analysis

机译:使用近红外光谱法检测高粱谷物中昆虫存在的非破坏性筛选方法,以及判别分析

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摘要

The potential of near-infrared spectroscopy (NIRS) combined with partial least squares discriminant analysis (PIS-DA) to develop a screening method for distinguishing uninfested from infested sorghum (Sorghum bicolour (L.) Moench) grains was for the first time investigated. A total of 108 sorghum grain samples from thirty-six different genotypes were infested with seventy Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae) unsexed adult insects during seventy days. More 101 uninfested sorghum grain samples from these same genotypes were used to build models. Principal components analysis (PCA) allowed slightly discriminating between the two classes along principal component two. A PIS-DA model presented perfect classification rates, with sensitivity and specificity equal to 100% for the test set. In addition, the model showed high accuracy, and accordance and concordance (precision) both equal to 100%. These results showed that the combination of NIBS with PLS-DA provided a rapid, cost-effective and non-invasive way to detect insect infestation in sorghum grains.
机译:近红外光谱(NIRS)与部分最小二乘判别分析(PIS-DA)的潜力组合用于开发用于区分从侵扰高粱(高粱双色(L.)Moench)颗粒的筛选方法的筛选方法是第一次研究。在七十天内,共有来自36种不同基因型的108种来自三六种不同基因型的高粱谷物样品患有七十米梨杆菌Zeamais Motschulsky(Coleoptera:Curculionidae)。更多101种未捕获的来自这些相同基因型的高粱谷物样品用于构建模型。主成分分析(PCA)允许沿主组件两种级别略微区分。 PIS-DA模型提出了完美的分类速率,灵敏度和特异性等于测试集的100%。此外,该模型表现出高精度,并按照等于100%的协调(精确度)。这些结果表明,具有PLS-DA的尖端的组合提供了一种快速,成本效益和非侵入性的方式来检测高粱谷物中的虫害。

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